'''simple docstring'''




import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__UpperCAmelCase					=logging.get_logger(__name__)


__UpperCAmelCase					={
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

__UpperCAmelCase					={
    "vocab_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"
    },
    "merges_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"
    },
    "tokenizer_config_file": {
        "facebook/blenderbot_small-90M": (
            "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"
        )
    },
}

__UpperCAmelCase					={"facebook/blenderbot_small-90M": 5_1_2}






def __lowerCAmelCase					(				UpperCamelCase__							)      ->       List[Any]:
    __lowerCamelCase            =    set()
    __lowerCamelCase            =    word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)							)
        __lowerCamelCase            =    char

    __lowerCamelCase            =    set(UpperCamelCase__							)
    return pairs




class        a__ (  UpperCAmelCase__					):
     lowerCamelCase    :	List[Any]				=VOCAB_FILES_NAMES
     lowerCamelCase    :	Tuple				=PRETRAINED_VOCAB_FILES_MAP
     lowerCamelCase    :	int				=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCamelCase    :	int				=["input_ids", "attention_mask"]






     def __init__(					self						:						List[Any]    ,							a						:						str    ,							a						:						Any    ,							a						:						List[str]="__start__"    ,							a						:						List[Any]="__end__"    ,							a						:						Optional[Any]="__unk__"    ,							a						:						int="__null__"    ,							**a						:						Union[str, Any]    ,							):





         """simple docstring"""



         super().__init__(unk_token=a    ,							bos_token=a    ,							eos_token=a    ,							pad_token=a    ,							**a       )

         with open(a    ,							encoding='''utf-8'''       ) as vocab_handle:
             __lowerCamelCase            =    json.load(a       )
         __lowerCamelCase            =    {v: k for k, v in self.encoder.items()}
         with open(a    ,							encoding='''utf-8'''       ) as merges_handle:
             __lowerCamelCase            =    merges_handle.read().split('''\n'''       )[1:-1]
         __lowerCamelCase            =    [tuple(merge.split()       ) for merge in merges]
         __lowerCamelCase            =    dict(zip(a    ,							range(len(a       )       )       )       )
         __lowerCamelCase            =    {}






     @property
     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[int]       ):





         """simple docstring"""



         return len(self.encoder       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						List[Any]       ):





         """simple docstring"""



         return dict(self.encoder    ,							**self.added_tokens_encoder       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[Any]    ,							a						:						str       ):





         """simple docstring"""



         if token in self.cache:
             return self.cache[token]
         __lowerCamelCase            =    re.sub('''([.,!?()])'''    ,							R''' \1'''    ,							a       )
         __lowerCamelCase            =    re.sub('''(\')'''    ,							R''' \1 '''    ,							a       )
         __lowerCamelCase            =    re.sub(R'''\s{2,}'''    ,							''' '''    ,							a       )
         if "\n" in token:
             __lowerCamelCase            =    token.replace('''\n'''    ,							''' __newln__'''       )

         __lowerCamelCase            =    token.split(''' '''       )
         __lowerCamelCase            =    []
         for token in tokens:
             if not len(a       ):
                 continue

             __lowerCamelCase            =    token.lower()
             __lowerCamelCase            =    tuple(a       )
             __lowerCamelCase            =    tuple(list(word[:-1]       ) + [word[-1] + '''</w>''']       )
             __lowerCamelCase            =    get_pairs(a       )

             if not pairs:
                 words.append(a       )
                 continue

             while True:
                 __lowerCamelCase            =    min(a    ,							key=lambda a       : self.bpe_ranks.get(a    ,							float('''inf'''       )       )       )
                 if bigram not in self.bpe_ranks:
                     break
                 __lowerCamelCase      ,    __lowerCamelCase            =    bigram
                 __lowerCamelCase            =    []
                 __lowerCamelCase            =    0

                 while i < len(a       ):
                     try:
                         __lowerCamelCase            =    word.index(a    ,							a       )
                         new_word.extend(word[i:j]       )
                         __lowerCamelCase            =    j
                     except ValueError:
                         new_word.extend(word[i:]       )
                         break

                     if word[i] == first and i < len(a       ) - 1 and word[i + 1] == second:
                         new_word.append(first + second       )
                         i += 2
                     else:
                         new_word.append(word[i]       )
                         i += 1
                 __lowerCamelCase            =    tuple(a       )
                 __lowerCamelCase            =    new_word
                 if len(a       ) == 1:
                     break
                 else:
                     __lowerCamelCase            =    get_pairs(a       )
             __lowerCamelCase            =    '''@@ '''.join(a       )
             __lowerCamelCase            =    word[:-4]

             __lowerCamelCase            =    word
             words.append(a       )
         return " ".join(a       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						List[str]    ,							a						:						str       ):





         """simple docstring"""



         __lowerCamelCase            =    []

         __lowerCamelCase            =    re.findall(R'''\S+\n?'''    ,							a       )

         for token in words:
             split_tokens.extend(list(self.bpe(a       ).split(''' '''       )       )       )
         return split_tokens






     def   SCREAMING_SNAKE_CASE__  (					self						:						str    ,							a						:						str       ):





         """simple docstring"""



         __lowerCamelCase            =    token.lower()
         return self.encoder.get(a    ,							self.encoder.get(self.unk_token       )       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						int    ,							a						:						int       ):





         """simple docstring"""



         return self.decoder.get(a    ,							self.unk_token       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						str    ,							a						:						List[str]       ):





         """simple docstring"""



         __lowerCamelCase            =    ''' '''.join(a       ).replace('''@@ '''    ,							''''''       ).strip()
         return out_string






     def   SCREAMING_SNAKE_CASE__  (					self						:						Union[str, Any]    ,							a						:						str    ,							a						:						Optional[str] = None       ):





         """simple docstring"""



         if not os.path.isdir(a       ):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""       )
             return
         __lowerCamelCase            =    os.path.join(
             a    ,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']       )
         __lowerCamelCase            =    os.path.join(
             a    ,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']       )

         with open(a    ,							'''w'''    ,							encoding='''utf-8'''       ) as f:
             f.write(json.dumps(self.encoder    ,							indent=2    ,							sort_keys=a    ,							ensure_ascii=a       ) + '''\n'''       )

         __lowerCamelCase            =    0
         with open(a    ,							'''w'''    ,							encoding='''utf-8'''       ) as writer:
             writer.write('''#version: 0.2\n'''       )
             for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,							key=lambda a       : kv[1]       ):
                 if index != token_index:
                     logger.warning(
                         f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
                         ''' Please check that the tokenizer is not corrupted!'''       )
                     __lowerCamelCase            =    token_index
                 writer.write(''' '''.join(a       ) + '''\n'''       )
                 index += 1

         return vocab_file, merge_file

'''simple docstring'''




import unittest
from typing import Tuple

import torch

from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch




@require_torch
class        a__ :






     @property
     def   SCREAMING_SNAKE_CASE__  (					self						:						str       ):





         """simple docstring"""



         return self.get_dummy_input()






     @property
     def   SCREAMING_SNAKE_CASE__  (					self						:						str       ):





         """simple docstring"""



         if self.block_type == "down":
             return (4, 32, 16, 16)
         elif self.block_type == "mid":
             return (4, 32, 32, 32)
         elif self.block_type == "up":
             return (4, 32, 64, 64)

         raise ValueError(f"""'{self.block_type}' is not a supported block_type. Set it to 'up', 'mid', or 'down'."""       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[Any]    ,							a						:						List[Any]=True    ,							a						:						Dict=False    ,							a						:						Optional[Any]=False    ,							a						:						List[Any]=False    ,							):





         """simple docstring"""



         __lowerCamelCase            =    4
         __lowerCamelCase            =    32
         __lowerCamelCase            =    (32, 32)

         __lowerCamelCase            =    torch.manual_seed(0       )
         __lowerCamelCase            =    torch.device(a       )
         __lowerCamelCase            =    (batch_size, num_channels) + sizes
         __lowerCamelCase            =    randn_tensor(a    ,							generator=a    ,							device=a       )
         __lowerCamelCase            =    {'''hidden_states''': hidden_states}

         if include_temb:
             __lowerCamelCase            =    1_28
             __lowerCamelCase            =    randn_tensor((batch_size, temb_channels)    ,							generator=a    ,							device=a       )

         if include_res_hidden_states_tuple:
             __lowerCamelCase            =    torch.manual_seed(1       )
             __lowerCamelCase            =    (randn_tensor(a    ,							generator=a    ,							device=a       ),)

         if include_encoder_hidden_states:
             __lowerCamelCase            =    floats_tensor((batch_size, 32, 32)       ).to(a       )

         if include_skip_sample:
             __lowerCamelCase            =    randn_tensor(((batch_size, 3) + sizes)    ,							generator=a    ,							device=a       )

         return dummy_input






     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[int]       ):





         """simple docstring"""



         __lowerCamelCase            =    {
             '''in_channels''': 32,
             '''out_channels''': 32,
             '''temb_channels''': 1_28,
         }
         if self.block_type == "up":
             __lowerCamelCase            =    32

         if self.block_type == "mid":
             init_dict.pop('''out_channels'''       )

         __lowerCamelCase            =    self.dummy_input
         return init_dict, inputs_dict






     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[Any]    ,							a						:						List[str]       ):





         """simple docstring"""



         __lowerCamelCase      ,    __lowerCamelCase            =    self.prepare_init_args_and_inputs_for_common()
         __lowerCamelCase            =    self.block_class(**a       )
         unet_block.to(a       )
         unet_block.eval()

         with torch.no_grad():
             __lowerCamelCase            =    unet_block(**a       )

         if isinstance(a    ,							a       ):
             __lowerCamelCase            =    output[0]

         self.assertEqual(output.shape    ,							self.output_shape       )

         __lowerCamelCase            =    output[0, -1, -3:, -3:]
         __lowerCamelCase            =    torch.tensor(a       ).to(a       )
         assert torch_all_close(output_slice.flatten()    ,							a    ,							atol=5e-3       )






     @unittest.skipIf(torch_device == '''mps'''    ,							'''Training is not supported in mps'''       )
     def   SCREAMING_SNAKE_CASE__  (					self						:						Any       ):





         """simple docstring"""



         __lowerCamelCase      ,    __lowerCamelCase            =    self.prepare_init_args_and_inputs_for_common()
         __lowerCamelCase            =    self.block_class(**a       )
         model.to(a       )
         model.train()
         __lowerCamelCase            =    model(**a       )

         if isinstance(a    ,							a       ):
             __lowerCamelCase            =    output[0]

         __lowerCamelCase            =    torch.device(a       )
         __lowerCamelCase            =    randn_tensor(output.shape    ,							device=a       )
         __lowerCamelCase            =    torch.nn.functional.mse_loss(a    ,							a       )
         loss.backward()
